Application of Earthquake Resistance Analysis Technique in the Design of Constructional Engineering

Abstract:

In recent years, frequent earthquakes have caused great casualties and economic losses in China. And in the earthquake, damage of buildings and the collapse is the main reason causing casualties. Therefore, in the design of constructional engineering, a seismicity of architectural structure is the pressing task at issue. Through time history analysis method, this paper analyzes the time history of building structural response and then it predicts the peak response of mode by response spectrum analysis. Based on this, this paper constructs a numerical simulation model for the architecture by using finite element analysis software SATWE. At the same time, this paper also calculates the structure seismic so as to determine the design of each function structure in architectural engineering design and then provides reference for the realization of earthquake-resistant building.

• Periodical: Advanced Materials Research (Volumes 756-759)
• Pages: 4482-4486
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.756-759.4482
• Online since: September 2013
• Authors: Chun Gan, Xue Song Luo
• Keywords: Architectural Design, Existing Residential Building, Finite Element Analysis Software SATWE, Response Spectrum Analysis Method, Seismic Structure, Simulation Model, Time-History Analysis

References

[1] Bilal Succar, Building information modelling framework: A research and delivery foundation for industry stakeholders, Automation in Construction, Vol. 18, No. 3, pp.357-375, (2009).

DOI: 10.1016/j.autcon.2008.10.003

[2] Tomo Cerovsek, A review and outlook for a 'Building Information Model' (BIM): A multi-standpoint framework for technological development , Advanced Engineering Informatics, Vol. 25, No. 2, pp.224-244, (2011).

DOI: 10.1016/j.aei.2010.06.003

[3] Zhenzhong Hu, Jianping Zhang, Ziyin Deng, Construction Process Simulation and Safety Analysis Based on Building Information Model and 4D Technology, Tsinghua Science & Technology, Vol. 13, pp.266-272, 20 08.

DOI: 10.1016/s1007-0214(08)70160-3

[4] Pingbo Tang, Daniel Huber, Burcu Akinci, Robert Lipman, Alan Lytle, Automatic reconstruction of as-built building information models from laser-scanned point clouds: A review of related techniquesy, Tsinghua Science & Technology, Vol. 19, No. 7, pp.829-843, (2010).

DOI: 10.1016/j.autcon.2010.06.007

[5] Sijie Zhang, Jochen Teizer, Jin-Kook Lee, Charles M. Eastman, Building Information Modeling (BIM) and Safety: Automatic Safety Checking of Construction Models and Schedules, Automation in Construction, Vol. 14, pp.183-195, (2013).

DOI: 10.1016/j.autcon.2012.05.006

[6] Nancy D. Rottle, Factors in the landscape-based greenway: a Mountains to Sound case study, Landscape and Urban Planning, Vol. 76, No. 1–4, pp.134-171, (2006).

DOI: 10.1016/j.landurbplan.2004.09.039

[7] Randy Gimblett, Linking perception research, visual simulations and dynamic modeling within a GIS framework: The ball state experience, Computers, Environment and Urban Systems, Vol. 13, No. 12, pp.109-123, (2009).

DOI: 10.1016/0198-9715(89)90038-0

[8] Lakshitha de Silva, Dharini Balasubramaniam, Controlling software architecture erosion: A survey, Journal of Systems and Software, Vol. 85, No. 1, pp.132-151, (2012).

DOI: 10.1016/j.jss.2011.07.036

[9] Sylvain Paquette, Gérald Domon, Changing ruralities, changing landscapes: exploring social recomposition using a multi-scale approach, Journal of Rural Studies, Vol. 19, No. 4, pp.425-444, (2006).

DOI: 10.1016/s0743-0167(03)00006-8

[10] Justin G. Ryan, John A. Ludwig, Clive A. Mcalpine, ex adaptive landscapes (CAL): A conceptual framework of multi-functional, non-linear ecohydrological feedback systems, Ecological Complexity, Vol. 4, No. 3, pp.113-127, (2007).

DOI: 10.1016/j.ecocom.2007.03.004

[11] Robert M. Scheller, James B. Domingo, Brian R. Sturtevant, Design, development, and application of LANDIS-II, a spatial landscape simulation model with flexible temporal and spatial resolution, Ecological Modelling, Vol. 201, No. 3–4, pp.409-419, (2007).

DOI: 10.1016/j.ecolmodel.2006.10.009